A method, system and medium for automatically inspecting moving targets based on laser scanner

Abstract

The present application provides a method, system and medium for automatic inspection of mobile targets based on laser scanners. The method includes: collecting and extracting the initial point cloud information of the mobile target, obtaining the feature data of the mobile target, and screening out the marked mobile target through threshold comparison, obtaining meteorological data and environmental data and evaluating the complexity of the meteorological environment to obtain the meteorological environment interference index; obtaining the feature data of the marked mobile target, combining the meteorological environment interference index to obtain the target characteristic recognition index, processing the road attribute data and the road characteristic data to obtain the road attribute calibration index, further combining the target characteristic recognition index to perform compliance evaluation to obtain the target road matching index; comparing the marked road matching index with the threshold, and issuing an alarm for those that do not meet the threshold comparison requirements, reminding the mobile target to adjust the road it is on, thereby realizing the technology of automatic inspection of mobile targets based on laser scanners.

Description

Technical Field

[0001] The present application relates to the technical field of automatic inspection of moving targets, and in particular, to a method, system and medium for automatic inspection of moving targets based on a laser scanner. Background Art

[0002] Inspection of moving targets, especially high-speed moving targets such as vehicles, needs to be completed without interrupting traffic.

[0003] At present, laser scanners play a vital role in the automatic inspection of moving targets. However, there are still many problems in the process of using laser scanners for automatic inspection of moving targets, such as how to improve the inspection accuracy and high pass rate. In addition, how to complete the automatic inspection work in complex environments and bad weather conditions while ensuring high accuracy and high efficiency remains to be solved.

[0004] In view of the above problems, effective technical solutions are urgently needed. Summary of the invention

[0005] The purpose of the present application is to provide a method, system and medium for automatic inspection of moving targets based on a laser scanner. The method can obtain marked moving targets through preliminary screening, improve the accuracy of automatic inspection, and then analyze and process the marked moving targets to obtain the target road matching index, thereby ensuring high accuracy and efficiency of the inspection. For those that do not meet the threshold requirements, an alarm message is generated and the mobile target is reminded to adjust the road it is on. In this way, high-speed moving objects can be monitored without interrupting traffic, ensuring that the mobile target complies with traffic regulations, and realizing a technology for automatic inspection of moving targets based on a laser scanner.

[0006] The present application also provides a method for automatically inspecting a moving target based on a laser scanner, comprising the following steps:

[0007] The initial point cloud information of the mobile target is collected through the preset laser monitoring platform, and the data of the initial point cloud information is extracted to obtain the characteristic data of the mobile target, including the shape size data, thermal imaging characteristic data and audio characteristic data of the mobile target, and the mobile target is screened out and marked through threshold comparison;

[0008] Acquire meteorological data and environmental data of the area where the marked mobile target is located, perform meteorological environment complexity assessment based on the meteorological data and environmental data, and obtain a meteorological environment interference index;

[0009] Acquiring characteristic data of the marked mobile target, and evaluating the target recognition degree according to the characteristic data combined with the meteorological environment interference index to obtain a target characteristic recognition index;

[0010] Acquire road surface attribute data and road surface characteristic data of the road where the marked moving target is located, and process the road surface attribute data in combination with the road surface characteristic data to obtain a road attribute calibration index of the road;

[0011] According to the target characteristic recognition index and the road attribute calibration index, the target road conformity evaluation is performed to obtain the target road matching index;

[0012] The target road matching index is compared with a preset target road matching threshold. If the threshold comparison result does not meet the preset threshold comparison requirement, an alarm is issued to remind the mobile target to adjust the road it is on.

[0013] Optionally, in the method for automatically inspecting a moving target based on a laser scanner described in the present application, the initial point cloud information of the moving target is collected by a preset laser monitoring platform, and data is extracted from the initial point cloud information to obtain feature data of the moving target, including the shape dimension data, thermal imaging feature data and audio feature data of the moving target, and the marking of the moving target is screened out by threshold comparison, including:

[0014] Collecting initial point cloud information of the moving target through a preset laser monitoring platform, including initial spatial coordinate information, initial timestamp information, initial normal vector information, initial point cloud density information, initial temperature value information and initial audio signal information;

[0015] Processing the initial point cloud information through a preset mobile target feature description model to obtain feature data of the mobile target, including shape dimension data, thermal imaging feature data, and audio feature data;

[0016] Acquire a preset condition threshold set of the mobile target, wherein the preset condition threshold set includes a preset size threshold, a preset thermal imaging feature threshold, and a preset audio feature threshold;

[0017] Compare the characteristic data with the three thresholds of the preset condition threshold set;

[0018] If the three items of the characteristic data are all greater than the corresponding thresholds of the preset condition threshold set, the moving target is marked as a marked moving target.

[0019] Optionally, in the method for automatic inspection of moving targets based on a laser scanner described in the present application, the step of acquiring meteorological data and environmental data of the area where the marked moving target is located, and performing a meteorological environment complexity assessment based on the meteorological data and environmental data to obtain a meteorological environment interference index includes:

[0020] Acquire meteorological data and environmental data of the area where the marked mobile target is located through a preset meteorological and environmental data monitoring platform database, wherein the meteorological data includes temperature data, precipitation data, wind speed data, and sunshine intensity data, and the environmental data includes air quality data and noise data;

[0021] According to the temperature data, precipitation data, wind speed data and sunshine intensity data, combined with the air quality data and noise data, the meteorological environment complexity assessment is performed to obtain a meteorological environment interference index;

[0022] The calculation formula of the meteorological environment interference index is:

[0023] ;

[0024] in, is the meteorological environment interference index, , , , They are temperature data, precipitation data, wind speed data, and sunshine intensity data. , They are air quality data and noise data respectively. , , , , , is the preset characteristic coefficient.

[0025] Optionally, in the method for automatic inspection of moving targets based on a laser scanner described in the present application, acquiring feature data of the marked moving target, and performing target recognition evaluation based on the feature data in combination with the meteorological environment interference index to obtain a target characteristic recognition index includes:

[0026] Acquiring characteristic data of the marked moving target through a preset laser scanning data monitoring platform database, including target size data, target moving speed data, target moving direction data, target reflection intensity data, and target reflectivity data;

[0027] According to the target size data, target moving speed data, target moving direction data, target reflection intensity data and target reflectivity data, combined with the meteorological environment interference index, target recognition degree evaluation is performed to obtain a target characteristic recognition index;

[0028] The calculation formula of the target characteristic recognition index is:

[0029] ;

[0030] in, is the target feature identification index, , , , , They are target size data, target moving speed data, target moving direction data, target reflection intensity data, and target reflectivity data. is the meteorological environment interference index, , , , , , is the preset characteristic coefficient.

[0031] Optionally, in the method for automatic inspection of moving targets based on a laser scanner described in the present application, the step of acquiring the pavement attribute data and pavement feature data of the road where the marked moving target is located, and performing processing based on the pavement attribute data in combination with the pavement feature data to obtain a road attribute calibration index of the road includes:

[0032] Acquire the pavement attribute data and pavement characteristic data of the road where the marked moving target is located through a preset road characteristic monitoring platform database;

[0033] Pavement attribute data include pavement type data, pavement age data, and pavement traffic flow data;

[0034] The pavement characteristic data includes pavement geometric characteristic data and pavement bearing capacity characteristic data;

[0035] The road attribute data is combined with the road feature data and processed through a preset road attribute evaluation model to obtain a road attribute calibration index for the road.

[0036] Optionally, in the automatic inspection method for moving targets based on a laser scanner described in the present application, the target road conformity evaluation is performed according to the target characteristic recognition index combined with the road attribute calibration index to obtain the target road matching index, including:

[0037] According to the target characteristic recognition index and the road attribute calibration index, a target road conformity evaluation is performed through a preset road matching evaluation model to obtain a target road matching index;

[0038] The calculation formula of the target road matching index is:

[0039] ;

[0040] in, is the target road matching index, , They are target feature recognition index and road attribute calibration index respectively. , is the preset characteristic coefficient.

[0041] In a second aspect, the present application provides a system for automatically inspecting a moving target based on a laser scanner, the system comprising: a memory and a processor, the memory comprising a program for automatically inspecting a moving target based on a laser scanner, the program for automatically inspecting a moving target based on a laser scanner being executed by the processor to implement the following steps:

[0042] The initial point cloud information of the mobile target is collected through the preset laser monitoring platform, and the data of the initial point cloud information is extracted to obtain the characteristic data of the mobile target, including the shape size data, thermal imaging characteristic data and audio characteristic data of the mobile target, and the mobile target is screened out and marked through threshold comparison;

[0043] Acquire meteorological data and environmental data of the area where the marked mobile target is located, perform meteorological environment complexity assessment based on the meteorological data and environmental data, and obtain a meteorological environment interference index;

[0044] Acquiring characteristic data of the marked mobile target, and evaluating the target recognition degree according to the characteristic data combined with the meteorological environment interference index to obtain a target characteristic recognition index;

[0045] Acquire road surface attribute data and road surface characteristic data of the road where the marked moving target is located, and process the road surface attribute data in combination with the road surface characteristic data to obtain a road attribute calibration index of the road;

[0046] According to the target characteristic recognition index and the road attribute calibration index, the target road conformity evaluation is performed to obtain the target road matching index;

[0047] The target road matching index is compared with a preset target road matching threshold. If the threshold comparison result does not meet the preset threshold comparison requirement, an alarm is issued to remind the mobile target to adjust the road it is on.

[0048] Optionally, in the automatic inspection system for moving targets based on laser scanners described in the present application, the initial point cloud information of the moving target is collected by a preset laser monitoring platform, and data is extracted from the initial point cloud information to obtain feature data of the moving target, including the shape size data, thermal imaging feature data and audio feature data of the moving target, and the moving target is marked by screening out the mark through threshold comparison, including:

[0049] Collecting initial point cloud information of the moving target through a preset laser monitoring platform, including initial spatial coordinate information, initial timestamp information, initial normal vector information, initial point cloud density information, initial temperature value information and initial audio signal information;

[0050] Processing the initial point cloud information through a preset mobile target feature description model to obtain feature data of the mobile target, including shape dimension data, thermal imaging feature data, and audio feature data;

[0051] Acquire a preset condition threshold set of the mobile target, wherein the preset condition threshold set includes a preset size threshold, a preset thermal imaging feature threshold, and a preset audio feature threshold;

[0052] Compare the characteristic data with the three thresholds of the preset condition threshold set;

[0053] If the three items of the characteristic data are all greater than the corresponding thresholds of the preset condition threshold set, the moving target is marked as a marked moving target.

[0054] Optionally, in the automatic inspection system for moving targets based on a laser scanner described in the present application, the step of acquiring meteorological data and environmental data of the area where the marked moving target is located, and performing a meteorological environment complexity assessment based on the meteorological data and environmental data to obtain a meteorological environment interference index includes:

[0055] Acquire meteorological data and environmental data of the area where the marked mobile target is located through a preset meteorological and environmental data monitoring platform database, wherein the meteorological data includes temperature data, precipitation data, wind speed data, and sunshine intensity data, and the environmental data includes air quality data and noise data;

[0056] According to the temperature data, precipitation data, wind speed data and sunshine intensity data, combined with the air quality data and noise data, the meteorological environment complexity assessment is performed to obtain a meteorological environment interference index;

[0057] The calculation formula of the meteorological environment interference index is:

[0058] ;

[0059] in, is the meteorological environment interference index, , , , They are temperature data, precipitation data, wind speed data, and sunshine intensity data. , They are air quality data and noise data respectively. , , , , , is the preset characteristic coefficient.

[0060] In a third aspect, the present application also provides a computer-readable storage medium, which stores a program for a method for automatically inspecting moving targets based on a laser scanner. When the program for automatically inspecting moving targets based on a laser scanner is executed by a processor, the steps of the method for automatically inspecting moving targets based on a laser scanner as described in any one of the above items are implemented.

[0061] As can be seen from the above, the method, system and medium for automatic inspection of mobile targets based on laser scanners provided in the present application obtain the feature data of the mobile target, including the shape dimension data, thermal imaging feature data and audio feature data of the mobile target, by collecting the initial point cloud information of the mobile target and performing data extraction, and screen out the marked mobile target through threshold comparison, obtain meteorological data and environmental data and perform meteorological environment complexity assessment to obtain the meteorological environment interference index; obtain the feature data of the marked mobile target, and obtain the target characteristic recognition index in combination with the meteorological environment interference index, and process the road surface attribute data in combination with the road surface characteristic data to obtain the road attribute calibration index, and further perform compliance assessment in combination with the target characteristic recognition index to obtain the target road matching index; compare the marked road matching index with the threshold, and issue an alarm for those that do not meet the threshold comparison requirements, reminding the mobile target to adjust the road it is on, thereby realizing the technology of automatic inspection of mobile targets based on laser scanners.

[0062] Other features and advantages of the present application will be described in the following description, and partly become apparent from the description, or understood by practicing the embodiments of the present application. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0064] Figure 1 A flowchart of a method for automatically inspecting a moving target based on a laser scanner provided in an embodiment of the present application;

[0065] Figure 2 A flowchart of screening out marked moving targets based on the automatic inspection method of moving targets by laser scanner provided in an embodiment of the present application;

[0066] Figure 3 A flow chart of obtaining a meteorological environment interference index based on a method for automatically inspecting a moving target using a laser scanner provided in an embodiment of the present application;

[0067] Figure 4 A flowchart of obtaining a target characteristic recognition index based on a method for automatically inspecting moving targets using a laser scanner is provided in an embodiment of the present application. DETAILED DESCRIPTION

[0068] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0069] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0070] Please refer to Figure 1 , Figure 1 The following is a flow chart of a method for automatically checking a moving target based on a laser scanner in some embodiments of the present application. The method for automatically checking a moving target based on a laser scanner is used in a terminal device, such as a computer, a mobile phone terminal, etc. The method for automatically checking a moving target based on a laser scanner comprises the following steps:

[0071] S11, collecting initial point cloud information of the mobile target through a preset laser monitoring platform, and extracting data from the initial point cloud information to obtain feature data of the mobile target, including shape dimension data, thermal imaging feature data, and audio feature data of the mobile target, and screening out and marking the mobile target through threshold comparison;

[0072] S12, obtaining meteorological data and environmental data of the area where the marked mobile target is located, performing a meteorological environment complexity assessment based on the meteorological data and environmental data, and obtaining a meteorological environment interference index;

[0073] S13, acquiring feature data of the marked mobile target, and performing target recognition evaluation based on the feature data in combination with the meteorological environment interference index to obtain a target characteristic recognition index;

[0074] S14, obtaining road surface attribute data and road surface feature data of the road where the marked moving target is located, and performing processing according to the road surface attribute data and the road surface feature data to obtain a road attribute calibration index of the road;

[0075] S15, evaluating the target road conformity according to the target characteristic recognition index combined with the road attribute calibration index to obtain a target road matching index;

[0076] S16. Compare the target road matching index with a preset target road matching threshold. If the threshold comparison result does not meet the preset threshold comparison requirement, issue an alarm to remind the mobile target to adjust the road.

[0077] It should be noted that the laser monitoring platform is a platform that integrates various types of laser scanners to monitor the information of mobile targets. In order to realize automatic inspection of mobile targets based on laser scanners, thereby completing automatic inspection of mobile targets, especially high-speed moving targets, and ensuring that mobile targets comply with traffic rules without interrupting traffic, the technology first collects the initial point cloud information of the mobile target and extracts data to obtain the feature data of the mobile target, including the shape size data, thermal imaging feature data and audio feature data of the mobile target, and screens out the marked mobile targets through threshold comparison, obtains meteorological data and environmental data, and performs meteorological environment complexity assessment to obtain the meteorological environment interference index; obtains the feature data of the marked mobile target, and obtains the target characteristic recognition index in combination with the meteorological environment interference index, processes the road surface attribute data in combination with the road surface characteristic data, obtains the road attribute calibration index, and further performs compliance assessment in combination with the target characteristic recognition index to obtain the target road matching index; compares the marked road matching index with the threshold, and issues an alarm for those that do not meet the threshold comparison requirements, reminding the mobile target to adjust the road it is on.

[0078] Please refer to Figure 2 , Figure 2 The flowchart of the method for automatically inspecting mobile targets based on a laser scanner in some embodiments of the present application is to screen out and mark mobile targets. According to the embodiment of the present invention, the initial point cloud information of the mobile target is collected by a preset laser monitoring platform, and the initial point cloud information is extracted to obtain the feature data of the mobile target, including the shape size data, thermal imaging feature data and audio feature data of the mobile target, and the mobile target is screened out and marked by threshold comparison, including:

[0079] S21, collecting initial point cloud information of the mobile target through a preset laser monitoring platform, including initial spatial coordinate information, initial timestamp information, initial normal vector information, initial point cloud density information, initial temperature value information and initial audio signal information;

[0080] S22, processing the initial point cloud information through a preset mobile target feature description model to obtain feature data of the mobile target, including shape dimension data, thermal imaging feature data, and audio feature data;

[0081] S23, obtaining a preset condition threshold set of the mobile target, wherein the preset condition threshold set includes a preset size threshold, a preset thermal imaging feature threshold, and a preset audio feature threshold;

[0082] S24, comparing the characteristic data with the three thresholds of the preset condition threshold set;

[0083] S25. If the three items of the characteristic data are all greater than the corresponding thresholds of the preset condition threshold set, the moving target is marked as a marked moving target.

[0084] It should be noted that before conducting a comprehensive and efficient automatic inspection of mobile targets, in order to improve accuracy, it is necessary to first screen the mobile targets to remove mobile targets that do not meet the preset requirements. First, three feature data of the mobile targets are obtained through existing multiple types of laser scanners, including shape dimension data, thermal imaging feature data and audio feature data, and compared with the existing corresponding preset thresholds. If these three feature data are all greater than the corresponding preset thresholds, then the mobile target will be marked as a marked mobile target and undergo the next stage of comprehensive monitoring and inspection.

[0085] Please refer to Figure 3 , Figure 3 The present invention is a flowchart of obtaining a meteorological environment interference index based on a laser scanner mobile target automatic inspection method in some embodiments of the present invention. According to an embodiment of the present invention, obtaining meteorological data and environmental data of the area where the marked mobile target is located, performing a meteorological environment complexity assessment based on the meteorological data and environmental data, and obtaining a meteorological environment interference index includes:

[0086] S31, obtaining meteorological data and environmental data of the area where the marked mobile target is located through a preset meteorological and environmental data monitoring platform database, wherein the meteorological data includes temperature data, precipitation data, wind speed data, and sunshine intensity data, and the environmental data includes air quality data and noise data;

[0087] S32, performing a meteorological environment complexity assessment based on the temperature data, precipitation data, wind speed data, and sunshine intensity data in combination with the air quality data and noise data to obtain a meteorological environment interference index;

[0088] The calculation formula of the meteorological environment interference index is:

[0089] ;

[0090] in, is the meteorological environment interference index, , , , They are temperature data, precipitation data, wind speed data, and sunshine intensity data. , They are air quality data and noise data respectively. , , , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset meteorological environment monitoring platform database).

[0091] It should be noted that the automatic inspection of mobile targets will be affected by environmental and meteorological interference, especially when the marked mobile targets are in complex environments and severe weather conditions. In order to improve the accuracy of automatic inspection and ensure the efficiency of inspection, it is necessary to fully consider the interference factors of the meteorological environment. Therefore, it is necessary to obtain the meteorological data and environmental data of the area where the marked mobile targets are located through the existing meteorological environment data monitoring platform database, and obtain the meteorological environment interference index through meteorological environment complexity assessment.

[0092] Please refer to Figure 4 , Figure 4 The present invention is a flowchart of obtaining a target characteristic recognition index based on a method for automatically inspecting a moving target using a laser scanner in some embodiments of the present invention. According to an embodiment of the present invention, the step of obtaining the characteristic data of the marked moving target and evaluating the target recognition degree based on the characteristic data in combination with the meteorological environment interference index to obtain the target characteristic recognition index includes:

[0093] S41, acquiring characteristic data of the marked moving target through a preset laser scanning data monitoring platform database, including target size data, target moving speed data, target moving direction data, target reflection intensity data, and target reflectivity data;

[0094] S42, performing target recognition evaluation based on the target size data, target moving speed data, target moving direction data, target reflection intensity data and target reflectivity data in combination with the meteorological environment interference index to obtain a target characteristic recognition index;

[0095] The calculation formula of the target characteristic recognition index is:

[0096] ;

[0097] in, is the target feature identification index, , , , , They are target size data, target moving speed data, target moving direction data, target reflection intensity data, and target reflectivity data. is the meteorological environment interference index, , , , , , is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset laser scanning monitoring platform database).

[0098] It should be noted that moving targets on the road can be divided into many types. Different types of moving targets have different characteristics. In order to identify the category characteristics of the marked moving targets, the characteristic data of the marked moving targets are first obtained through the existing laser scanning data monitoring platform database, including target size data, target moving speed data, target moving direction data, target reflection intensity data and target reflectivity data. Then, the target recognition degree is evaluated in combination with the meteorological environment interference index to obtain the target characteristic recognition index.

[0099] According to an embodiment of the present invention, the step of acquiring the pavement attribute data and pavement feature data of the road where the marked moving target is located, and performing processing according to the pavement attribute data in combination with the pavement feature data to obtain a road attribute calibration index of the road includes:

[0100] Acquire the pavement attribute data and pavement characteristic data of the road where the marked moving target is located through a preset road characteristic monitoring platform database;

[0101] Pavement attribute data include pavement type data, pavement age data, and pavement traffic flow data;

[0102] The pavement characteristic data includes pavement geometric characteristic data and pavement bearing capacity characteristic data;

[0103] The road attribute data is combined with the road feature data and processed through a preset road attribute evaluation model to obtain a road attribute calibration index for the road.

[0104] It should be noted that roads have different attributes. For example, highways have fast lanes, slow lanes and shoulders, and national highways have bus lanes. In order to identify the attributes of the road where the marked moving target is located, the pavement attribute data and pavement feature data of the road where the marked moving target is located are first obtained through the existing road characteristic monitoring platform database, and then the above data are input into the existing road attribute evaluation model for processing to obtain the road attribute calibration index of the road. Among them, the road attribute evaluation model is a neural network model. The initialized road attribute evaluation model is trained according to a large amount of historical pavement attribute data and pavement feature data to obtain a trained road attribute evaluation model.

[0105] According to an embodiment of the present invention, the target road conformity evaluation is performed according to the target characteristic recognition index in combination with the road attribute calibration index to obtain the target road matching index, including:

[0106] According to the target characteristic recognition index and the road attribute calibration index, a target road conformity evaluation is performed through a preset road matching evaluation model to obtain a target road matching index;

[0107] The calculation formula of the target road matching index is:

[0108] ;

[0109] in, is the target road matching index, , They are target feature recognition index and road attribute calibration index respectively. , is the preset characteristic coefficient. (The characteristic coefficient is obtained by querying the preset laser scanning monitoring platform database).

[0110] It should be noted that after obtaining the target characteristic recognition index of the marked mobile target and the corresponding road attribute calibration index, it is necessary to further determine whether the road on which the marked mobile target is located meets the requirements of traffic regulations. Therefore, it is necessary to evaluate the target road conformity based on the target characteristic recognition index of the marked mobile target and the road attribute calibration index through the calculation formula of the existing road matching evaluation model to obtain the target road matching index.

[0111] According to an embodiment of the present invention, the method further includes:

[0112] Obtaining a road attribute calibration index of the road where the marked moving target is located;

[0113] Determining whether the road classification index is within a preset parking prohibition calibration threshold range;

[0114] If so, determining whether the target characteristic recognition index of the marked moving target is within a preset special characteristic threshold range;

[0115] If not, obtaining the motion state information of the marked moving target, and determining whether the motion state information is within a first preset state threshold interval;

[0116] If it is, obtain the time data corresponding to the motion state information, compare the time data with a preset time threshold, and if the comparison result does not meet the preset range, issue an alarm to remind the marked moving target to leave the road.

[0117] It should be noted that when it is identified that the road where the marked moving target is located is a no-parking road, such as the exit of a fire passage, it is determined whether the moving target is a special target, such as an ambulance, fire truck or police car. If not, the motion state information of the moving target is further determined. When the motion state is in the first preset state threshold interval, this embodiment takes the threshold interval as 0-0.2, and starts to calculate the time data of the moving target on the no-parking road. When the time data exceeds the preset threshold, an alarm is issued to remind the marked moving target to leave the road.

[0118] According to an embodiment of the present invention, the method further includes:

[0119] Collecting monitoring information of the marked moving target, including speed information, position information, shape information and contour information;

[0120] Extracting characteristic data according to the monitoring information, including velocity change rate data, acceleration change rate data, direction change rate data, and target profile change amount data;

[0121] Performing a deviation evaluation based on the speed change rate data, the acceleration change rate data, the direction change rate data, and the target profile change amount data to obtain a target state deviation index of the marked moving target;

[0122] Comparing the target condition deviation index with a preset target condition matching threshold, if the threshold comparison result does not meet the preset threshold comparison requirement, issuing an alarm to remind the rescue center to perform road rescue for the marked moving target;

[0123] The calculation formula of the target condition deviation index is:

[0124] ;

[0125] in, is the target status deviation index, , , , They are velocity change rate data, acceleration change rate data, direction change rate data, and target profile change data. , , , is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset laser scanning monitoring platform database).

[0126] It should be noted that when an abnormal situation occurs in a moving target, such as a traffic accident, it is necessary to promptly report the situation and implement road rescue. At this time, the speed, acceleration, movement direction and external contour of the moving target may change abnormally. Therefore, it is necessary to collect monitoring information of the marked moving target, including speed, position, shape and contour information, and extract feature data, including speed change rate, acceleration change rate, direction change rate and target contour change amount. Deviation evaluation is performed based on the above feature data to obtain the target condition deviation index of the marked moving target, and at the same time, it is compared with the preset target condition matching threshold to obtain the comparison result, and corresponding processing is performed based on the comparison result.

[0127] In a second aspect, the present invention further discloses a system for automatically inspecting a moving target based on a laser scanner, comprising a memory and a processor, wherein the memory comprises a program for automatically inspecting a moving target based on a laser scanner, and when the program for automatically inspecting a moving target based on a laser scanner is executed by the processor, the following steps are implemented:

[0128] The initial point cloud information of the mobile target is collected through the preset laser monitoring platform, and the data of the initial point cloud information is extracted to obtain the characteristic data of the mobile target, including the shape size data, thermal imaging characteristic data and audio characteristic data of the mobile target, and the mobile target is screened out and marked through threshold comparison;

[0129] Acquire meteorological data and environmental data of the area where the marked mobile target is located, perform meteorological environment complexity assessment based on the meteorological data and environmental data, and obtain a meteorological environment interference index;

[0130] Acquiring characteristic data of the marked mobile target, and evaluating the target recognition degree according to the characteristic data combined with the meteorological environment interference index to obtain a target characteristic recognition index;

[0131] Acquire road surface attribute data and road surface characteristic data of the road where the marked moving target is located, and process the road surface attribute data in combination with the road surface characteristic data to obtain a road attribute calibration index of the road;

[0132] According to the target characteristic recognition index and the road attribute calibration index, the target road conformity evaluation is performed to obtain the target road matching index;

[0133] The target road matching index is compared with a preset target road matching threshold. If the threshold comparison result does not meet the preset threshold comparison requirement, an alarm is issued to remind the mobile target to adjust the road it is on.

[0134] It should be noted that the laser monitoring platform is a platform that integrates various types of laser scanners to monitor the information of mobile targets. In order to realize automatic inspection of mobile targets based on laser scanners, thereby completing automatic inspection of mobile targets, especially high-speed moving targets, and ensuring that mobile targets comply with traffic rules without interrupting traffic, the technology first collects the initial point cloud information of the mobile target and extracts data to obtain the feature data of the mobile target, including the shape size data, thermal imaging feature data and audio feature data of the mobile target, and screens out the marked mobile targets through threshold comparison, obtains meteorological data and environmental data, and performs meteorological environment complexity assessment to obtain the meteorological environment interference index; obtains the feature data of the marked mobile target, and obtains the target characteristic recognition index in combination with the meteorological environment interference index, processes the road surface attribute data in combination with the road surface characteristic data, obtains the road attribute calibration index, and further performs compliance assessment in combination with the target characteristic recognition index to obtain the target road matching index; compares the marked road matching index with the threshold, and issues an alarm for those that do not meet the threshold comparison requirements, reminding the mobile target to adjust the road it is on.

[0135] According to an embodiment of the present invention, the initial point cloud information of the mobile target is collected by a preset laser monitoring platform, and data is extracted from the initial point cloud information to obtain feature data of the mobile target, including the shape size data, thermal imaging feature data and audio feature data of the mobile target, and the mobile target is marked by screening out the threshold comparison, including:

[0136] Collecting initial point cloud information of the moving target through a preset laser monitoring platform, including initial spatial coordinate information, initial timestamp information, initial normal vector information, initial point cloud density information, initial temperature value information and initial audio signal information;

[0137] Processing the initial point cloud information through a preset mobile target feature description model to obtain feature data of the mobile target, including shape dimension data, thermal imaging feature data, and audio feature data;

[0138] Acquire a preset condition threshold set of the mobile target, wherein the preset condition threshold set includes a preset size threshold, a preset thermal imaging feature threshold, and a preset audio feature threshold;

[0139] Compare the characteristic data with the three thresholds of the preset condition threshold set;

[0140] If the three items of the characteristic data are all greater than the corresponding thresholds of the preset condition threshold set, the moving target is marked as a marked moving target.

[0141] It should be noted that before conducting a comprehensive and efficient automatic inspection of mobile targets, in order to improve accuracy, it is necessary to first screen the mobile targets to remove mobile targets that do not meet the preset requirements. First, three feature data of the mobile targets are obtained through existing multiple types of laser scanners, including shape dimension data, thermal imaging feature data and audio feature data, and compared with the existing corresponding preset thresholds. If these three feature data are all greater than the corresponding preset thresholds, then the mobile target will be marked as a marked mobile target and undergo the next stage of comprehensive monitoring and inspection.

[0142] According to an embodiment of the present invention, the step of acquiring meteorological data and environmental data of the area where the marked mobile target is located, performing a meteorological environment complexity assessment based on the meteorological data and environmental data, and obtaining a meteorological environment interference index includes:

[0143] Acquire meteorological data and environmental data of the area where the marked mobile target is located through a preset meteorological and environmental data monitoring platform database, wherein the meteorological data includes temperature data, precipitation data, wind speed data, and sunshine intensity data, and the environmental data includes air quality data and noise data;

[0144] According to the temperature data, precipitation data, wind speed data and sunshine intensity data, combined with the air quality data and noise data, the meteorological environment complexity assessment is performed to obtain a meteorological environment interference index;

[0145] The calculation formula of the meteorological environment interference index is:

[0146] ;

[0147] in, is the meteorological environment interference index, , , , They are temperature data, precipitation data, wind speed data, and sunshine intensity data. , They are air quality data and noise data respectively. , , , , , It is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset meteorological environment monitoring platform database).

[0148] It should be noted that the automatic inspection of mobile targets will be affected by environmental and meteorological interference, especially when the marked mobile targets are in complex environments and severe weather conditions. In order to improve the accuracy of automatic inspection and ensure the efficiency of inspection, it is necessary to fully consider the interference factors of the meteorological environment. Therefore, it is necessary to obtain the meteorological data and environmental data of the area where the marked mobile targets are located through the existing meteorological environment data monitoring platform database, and obtain the meteorological environment interference index through meteorological environment complexity assessment.

[0149] According to an embodiment of the present invention, the step of acquiring the characteristic data of the marked mobile target and evaluating the target recognition degree according to the characteristic data in combination with the meteorological environment interference index to obtain the target characteristic recognition index includes:

[0150] Acquiring characteristic data of the marked moving target through a preset laser scanning data monitoring platform database, including target size data, target moving speed data, target moving direction data, target reflection intensity data, and target reflectivity data;

[0151] According to the target size data, target moving speed data, target moving direction data, target reflection intensity data and target reflectivity data, combined with the meteorological environment interference index, target recognition degree evaluation is performed to obtain a target characteristic recognition index;

[0152] The calculation formula of the target characteristic recognition index is:

[0153] ;

[0154] in, is the target feature identification index, , , , , They are target size data, target moving speed data, target moving direction data, target reflection intensity data, and target reflectivity data. is the meteorological environment interference index, , , , , , is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset laser scanning monitoring platform database).

[0155] It should be noted that moving targets on the road can be divided into many types. Different types of moving targets have different characteristics. In order to identify the category characteristics of the marked moving targets, the characteristic data of the marked moving targets are first obtained through the existing laser scanning data monitoring platform database, including target size data, target moving speed data, target moving direction data, target reflection intensity data and target reflectivity data. Then, the target recognition degree is evaluated in combination with the meteorological environment interference index to obtain the target characteristic recognition index.

[0156] According to an embodiment of the present invention, the step of acquiring the pavement attribute data and pavement feature data of the road where the marked moving target is located, and performing processing according to the pavement attribute data in combination with the pavement feature data to obtain a road attribute calibration index of the road includes:

[0157] Acquire the pavement attribute data and pavement characteristic data of the road where the marked moving target is located through a preset road characteristic monitoring platform database;

[0158] Pavement attribute data include pavement type data, pavement age data, and pavement traffic flow data;

[0159] The pavement characteristic data includes pavement geometric characteristic data and pavement bearing capacity characteristic data;

[0160] The road attribute data is combined with the road feature data and processed through a preset road attribute evaluation model to obtain a road attribute calibration index for the road.

[0161] It should be noted that roads have different attributes. For example, highways have fast lanes, slow lanes and shoulders, and national highways have bus lanes. In order to identify the attributes of the road where the marked moving target is located, the pavement attribute data and pavement feature data of the road where the marked moving target is located are first obtained through the existing road characteristic monitoring platform database, and then the above data are input into the existing road attribute evaluation model for processing to obtain the road attribute calibration index of the road. Among them, the road attribute evaluation model is a neural network model. The initialized road attribute evaluation model is trained according to a large amount of historical pavement attribute data and pavement feature data to obtain a trained road attribute evaluation model.

[0162] According to an embodiment of the present invention, the target road conformity evaluation is performed according to the target characteristic recognition index in combination with the road attribute calibration index to obtain the target road matching index, including:

[0163] According to the target characteristic recognition index and the road attribute calibration index, a target road conformity evaluation is performed through a preset road matching evaluation model to obtain a target road matching index;

[0164] The calculation formula of the target road matching index is:

[0165] ;

[0166] in, is the target road matching index, , They are target feature recognition index and road attribute calibration index respectively. , is the preset characteristic coefficient. (The characteristic coefficient is obtained by querying the preset laser scanning monitoring platform database).

[0167] It should be noted that after obtaining the target characteristic recognition index of the marked mobile target and the corresponding road attribute calibration index, it is necessary to further determine whether the road on which the marked mobile target is located meets the requirements of traffic regulations. Therefore, it is necessary to evaluate the target road conformity based on the target characteristic recognition index of the marked mobile target and the road attribute calibration index through the calculation formula of the existing road matching evaluation model to obtain the target road matching index.

[0168] According to an embodiment of the present invention, the method further includes:

[0169] Obtaining a road attribute calibration index of the road where the marked moving target is located;

[0170] Determining whether the road classification index is within a preset parking prohibition calibration threshold range;

[0171] If so, determining whether the target characteristic recognition index of the marked moving target is within a preset special characteristic threshold range;

[0172] If not, obtaining the motion state information of the marked moving target, and determining whether the motion state information is within a first preset state threshold interval;

[0173] If it is, obtain the time data corresponding to the motion state information, compare the time data with a preset time threshold, and if the comparison result does not meet the preset range, issue an alarm to remind the marked moving target to leave the road.

[0174] It should be noted that when it is identified that the road where the marked moving target is located is a no-parking road, such as the exit of a fire passage, it is determined whether the moving target is a special target, such as an ambulance, fire truck or police car. If not, the motion state information of the moving target is further determined. When the motion state is in the first preset state threshold interval, this embodiment takes the threshold interval as 0-0.2, and starts to calculate the time data of the moving target on the no-parking road. When the time data exceeds the preset threshold, an alarm is issued to remind the marked moving target to leave the road.

[0175] According to an embodiment of the present invention, the method further includes:

[0176] Collecting monitoring information of the marked moving target, including speed information, position information, shape information and contour information;

[0177] Extracting characteristic data according to the monitoring information, including velocity change rate data, acceleration change rate data, direction change rate data, and target profile change amount data;

[0178] Performing a deviation evaluation based on the speed change rate data, the acceleration change rate data, the direction change rate data, and the target profile change amount data to obtain a target state deviation index of the marked moving target;

[0179] Comparing the target condition deviation index with a preset target condition matching threshold, if the threshold comparison result does not meet the preset threshold comparison requirement, issuing an alarm to remind the rescue center to perform road rescue for the marked moving target;

[0180] The calculation formula of the target condition deviation index is:

[0181] ;

[0182] in, is the target status deviation index, , , , They are velocity change rate data, acceleration change rate data, direction change rate data, and target profile change data. , , , is the preset characteristic coefficient (the characteristic coefficient is obtained by querying the preset laser scanning monitoring platform database).

[0183] It should be noted that when an abnormal situation occurs in a moving target, such as a traffic accident, it is necessary to promptly report the situation and implement road rescue. At this time, the speed, acceleration, movement direction and external contour of the moving target may change abnormally. Therefore, it is necessary to collect monitoring information of the marked moving target, including speed, position, shape and contour information, and extract feature data, including speed change rate, acceleration change rate, direction change rate and target contour change amount. Deviation evaluation is performed based on the above feature data to obtain the target condition deviation index of the marked moving target, and at the same time, it is compared with the preset target condition matching threshold to obtain the comparison result, and corresponding processing is performed based on the comparison result.

[0184] A third aspect of the present invention provides a readable storage medium, which stores a program for a method for automatically inspecting moving targets based on a laser scanner. When the program for automatically inspecting moving targets based on a laser scanner is executed by a processor, the steps of the method for automatically inspecting moving targets based on a laser scanner as described in any one of the above items are implemented.

[0185] The present invention discloses a method, system and medium for automatic inspection of mobile targets based on a laser scanner. The method collects initial point cloud information of the mobile target and performs data extraction to obtain feature data of the mobile target, including shape dimension data, thermal imaging feature data and audio feature data of the mobile target, and screens out marked mobile targets through threshold comparison, obtains meteorological data and environmental data, and performs meteorological environment complexity assessment to obtain a meteorological environment interference index; obtains the feature data of the marked mobile target, obtains a target characteristic recognition index in combination with the meteorological environment interference index, processes the road surface attribute data in combination with the road surface characteristic data to obtain a road attribute calibration index, further performs compliance assessment in combination with the target characteristic recognition index to obtain a target road matching index; compares the marked road matching index with a threshold, and issues an alarm for those that do not meet the threshold comparison requirement, reminding the mobile target to adjust the road it is on, thereby realizing a technology for automatic inspection of mobile targets based on a laser scanner.

[0186] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0187] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0188] In addition, all functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may be separately used as a unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0189] Those skilled in the art can understand that: all or part of the steps of implementing the above method embodiments can be completed by hardware related to program instructions, the aforementioned program can be stored in a readable storage medium, and when the program is executed, it executes the steps of the above method embodiments; and the aforementioned storage medium includes: mobile storage devices, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), disks or optical disks, and other media that can store program codes.

[0190] Alternatively, if the above-mentioned integrated unit of the present invention is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present invention can be essentially or partly reflected in the form of a software product that contributes to the prior art. The software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROM, RAM, magnetic disks or optical disks.

Claims

1. A method for automatically inspecting moving targets based on a laser scanner, characterized in that: The following steps are involved: The initial point cloud information of the mobile target is collected through the preset laser monitoring platform, and the data of the initial point cloud information is extracted to obtain the characteristic data of the mobile target, including the shape size data, thermal imaging characteristic data and audio characteristic data of the mobile target, and the mobile target is screened out and marked through threshold comparison; Acquire meteorological data and environmental data of the area where the marked mobile target is located, perform meteorological environment complexity assessment based on the meteorological data and environmental data, and obtain a meteorological environment interference index; Acquiring characteristic data of the marked mobile target, and evaluating the target recognition degree according to the characteristic data combined with the meteorological environment interference index to obtain a target characteristic recognition index; Acquire road surface attribute data and road surface characteristic data of the road where the marked moving target is located, and process the road surface attribute data in combination with the road surface characteristic data to obtain a road attribute calibration index of the road; According to the target characteristic recognition index and the road attribute calibration index, the target road conformity evaluation is performed to obtain the target road matching index; The target road matching index is compared with a preset target road matching threshold. If the threshold comparison result does not meet the preset threshold comparison requirement, an alarm is issued to remind the mobile target to adjust the road it is on.

2. The method for automatically inspecting a moving target based on a laser scanner according to claim 1 is characterized in that: The initial point cloud information of the mobile target is collected by a preset laser monitoring platform, and data is extracted from the initial point cloud information to obtain feature data of the mobile target, including the shape size data, thermal imaging feature data and audio feature data of the mobile target, and the mobile target is marked by screening out the threshold comparison, including: Collecting initial point cloud information of the moving target through a preset laser monitoring platform, including initial spatial coordinate information, initial timestamp information, initial normal vector information, initial point cloud density information, initial temperature value information and initial audio signal information; Processing the initial point cloud information through a preset mobile target feature description model to obtain feature data of the mobile target, including shape dimension data, thermal imaging feature data, and audio feature data; Acquire a preset condition threshold set of the mobile target, wherein the preset condition threshold set includes a preset size threshold, a preset thermal imaging feature threshold, and a preset audio feature threshold; Compare the characteristic data with the three thresholds of the preset condition threshold set; If the three items of the characteristic data are all greater than the corresponding thresholds of the preset condition threshold set, the moving target is marked as a marked moving target.

3. The method for automatically inspecting a moving target based on a laser scanner according to claim 2 is characterized in that: The step of acquiring meteorological data and environmental data of the area where the marked mobile target is located, and performing a meteorological environment complexity assessment based on the meteorological data and environmental data to obtain a meteorological environment interference index includes: Acquire meteorological data and environmental data of the area where the marked mobile target is located through a preset meteorological and environmental data monitoring platform database, wherein the meteorological data includes temperature data, precipitation data, wind speed data, and sunshine intensity data, and the environmental data includes air quality data and noise data; According to the temperature data, precipitation data, wind speed data and sunshine intensity data, combined with the air quality data and noise data, the meteorological environment complexity assessment is performed to obtain a meteorological environment interference index; The calculation formula of the meteorological environment interference index is: ； in, is the meteorological environment interference index, , , , They are temperature data, precipitation data, wind speed data, and sunshine intensity data. , They are air quality data and noise data respectively. , , , , , is the preset characteristic coefficient.

4. The method for automatically inspecting a moving target based on a laser scanner according to claim 3 is characterized in that: The step of acquiring the characteristic data of the marked mobile target and evaluating the target recognition degree according to the characteristic data in combination with the meteorological environment interference index to obtain the target characteristic recognition index includes: Acquiring characteristic data of the marked moving target through a preset laser scanning data monitoring platform database, including target size data, target moving speed data, target moving direction data, target reflection intensity data, and target reflectivity data; According to the target size data, target moving speed data, target moving direction data, target reflection intensity data and target reflectivity data, combined with the meteorological environment interference index, target recognition degree evaluation is performed to obtain a target characteristic recognition index; The calculation formula of the target characteristic recognition index is: ； in, is the target feature identification index, , , , , They are target size data, target moving speed data, target moving direction data, target reflection intensity data, and target reflectivity data. is the meteorological environment interference index, , , , , , is the preset characteristic coefficient.

5. The method for automatically inspecting a moving target based on a laser scanner according to claim 4 is characterized in that: The step of acquiring the road surface attribute data and the road surface characteristic data of the road where the marked moving target is located, and performing processing according to the road surface attribute data in combination with the road surface characteristic data to obtain the road attribute calibration index of the road includes: Acquire the pavement attribute data and pavement characteristic data of the road where the marked moving target is located through a preset road characteristic monitoring platform database; Pavement attribute data include pavement type data, pavement age data, and pavement traffic flow data; The pavement characteristic data includes pavement geometric characteristic data and pavement bearing capacity characteristic data; The road attribute data is combined with the road feature data and processed through a preset road attribute evaluation model to obtain a road attribute calibration index for the road.

6. The method for automatically inspecting a moving target based on a laser scanner according to claim 5 is characterized in that: The target road conformity evaluation is performed according to the target characteristic recognition index in combination with the road attribute calibration index to obtain the target road matching index, including: According to the target characteristic recognition index and the road attribute calibration index, a target road conformity evaluation is performed through a preset road matching evaluation model to obtain a target road matching index; The calculation formula of the target road matching index is: ； in, is the target road matching index, , They are target feature recognition index and road attribute calibration index respectively. , is the preset characteristic coefficient.

7. A laser scanner based moving target automatic inspection system, characterized in that: The system includes: a memory and a processor, wherein the memory includes a program based on a method for automatically inspecting a moving target using a laser scanner, and when the program based on a method for automatically inspecting a moving target using a laser scanner is executed by the processor, the following steps are implemented: The initial point cloud information of the mobile target is collected through the preset laser monitoring platform, and the data of the initial point cloud information is extracted to obtain the characteristic data of the mobile target, including the shape size data, thermal imaging characteristic data and audio characteristic data of the mobile target, and the mobile target is screened out and marked through threshold comparison; Acquire meteorological data and environmental data of the area where the marked mobile target is located, perform meteorological environment complexity assessment based on the meteorological data and environmental data, and obtain a meteorological environment interference index; Acquiring characteristic data of the marked mobile target, and evaluating the target recognition degree according to the characteristic data combined with the meteorological environment interference index to obtain a target characteristic recognition index; Acquire road surface attribute data and road surface characteristic data of the road where the marked moving target is located, and process the road surface attribute data in combination with the road surface characteristic data to obtain a road attribute calibration index of the road; According to the target characteristic recognition index and the road attribute calibration index, the target road conformity evaluation is performed to obtain the target road matching index; The target road matching index is compared with a preset target road matching threshold. If the threshold comparison result does not meet the preset threshold comparison requirement, an alarm is issued to remind the mobile target to adjust the road it is on.

8. The automatic inspection system for moving targets based on laser scanner according to claim 7 is characterized in that: The initial point cloud information of the mobile target is collected by a preset laser monitoring platform, and data is extracted from the initial point cloud information to obtain feature data of the mobile target, including the shape size data, thermal imaging feature data and audio feature data of the mobile target, and the mobile target is marked by screening out the threshold comparison, including: Collecting initial point cloud information of the moving target through a preset laser monitoring platform, including initial spatial coordinate information, initial timestamp information, initial normal vector information, initial point cloud density information, initial temperature value information and initial audio signal information; Processing the initial point cloud information through a preset mobile target feature description model to obtain feature data of the mobile target, including shape dimension data, thermal imaging feature data, and audio feature data; Acquire a preset condition threshold set of the mobile target, wherein the preset condition threshold set includes a preset size threshold, a preset thermal imaging feature threshold, and a preset audio feature threshold; Compare the characteristic data with the three thresholds of the preset condition threshold set; If the three items of the characteristic data are all greater than the corresponding thresholds of the preset condition threshold set, the moving target is marked as a marked moving target.

9. The automatic inspection system for moving targets based on laser scanner according to claim 8 is characterized in that: The step of acquiring meteorological data and environmental data of the area where the marked mobile target is located, and performing a meteorological environment complexity assessment based on the meteorological data and environmental data to obtain a meteorological environment interference index includes: Acquire meteorological data and environmental data of the area where the marked mobile target is located through a preset meteorological and environmental data monitoring platform database, wherein the meteorological data includes temperature data, precipitation data, wind speed data, and sunshine intensity data, and the environmental data includes air quality data and noise data; According to the temperature data, precipitation data, wind speed data and sunshine intensity data, combined with the air quality data and noise data, the meteorological environment complexity assessment is performed to obtain a meteorological environment interference index; The calculation formula of the meteorological environment interference index is: ； in, is the meteorological environment interference index, , , , They are temperature data, precipitation data, wind speed data, and sunshine intensity data. , They are air quality data and noise data respectively. , , , , , is the preset characteristic coefficient.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a program of a method for automatically inspecting moving targets based on a laser scanner. When the program of the method for automatically inspecting moving targets based on a laser scanner is executed by a processor, the steps of the method for automatically inspecting moving targets based on a laser scanner as described in any one of claims 1 to 6 are implemented.

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